Sentimenal analysis

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Assalamualaikum steemians

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How are you?Hope so everyone would be safe and sound just like me as I am also safe Alhamdulillah....

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sentimental analysis is my today's topic to share with all of you guys so I would like to into its depth!

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If I talk about sentimental analysis then this is basically a small field of natural language processing which basically deals with automatic detecting and classifying of emotion, opinions and sentiments which are expressed in text data and when I talk about major and primary purpose of sentimental analysis then it is used for determination of piece of text which is conveying sentiment so what kind of sentiment text is conveying either it is positive ,negative or neutral can be determined by it.

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If I talk about multiple applications of sentiment analysis then it includes checking feedback from customers,analyzation of trends of market that either market is in upward trend or in downward trend as well as for identification of opinion of overall public at social media.

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if I talk about to basic approaches of sentiment analysis then first of all we have rule based and secondly we have machine learning based so if I talk about rule base get approach then it has its reliance at those rules and regulations that are predefined and that are used for identification of sentiment bearing phrases and when I talk about machine learning based approach then it is used different algorithms like support vector machine as well as random forest for classification of text that it is positive ,negative or neutral.

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If I talk about deep learning techniques then these are specifically recurrent neural networks as well as convolutional neural networks that have also apply to sentimental analysis in a successful way. There are different levels at which sentimental analysis can be performed the like sentence level ,document level as well as at aspect level etc.

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if I talk about aspect level sentimental analysis then it includes identification of sentiment towards some of the most particular features or aspects of any particular entity so there are also some of the major challenges in this type of analysis in which first of all is to manage irony as well as figurative languages as well as dealing with data which is incomplete.

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if I talk about importance of this type of analysis in digital age then it has a lot of importance at which online reviewing and social media posting can effect reputation of business in a significant way.For addressing challenges of this type of analysis there are researchers that have advanced some of the particular techniques like sentiment lexicons as well as machine learning algorithm etc.

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If I talk about machine learning algorithms then they can learn from labelled sets of data and enhancement of sentiment classification preciseness and if I talk about aspect based sentimental analysis then this is most specifically used in field of e-commerce in which customers most often comment at some of the particular product features. As an example you can understand that are customers is reviewing on a particular product so he can praise design of product but can criticize its battery life on other hand.

Example that I have gave above is important to understand because in these type of cases aspect base sentimental analysis can be used for identification of sentiment towards each aspect so regarding other applications of this type of analysis like in checking social media it can help for tracking opinion of public at different topics.

Now I want to conclude in such a way that when you analyse sentimental trends then it could be very helpful for different organisations and business for making precise decision and for adjusting their strategies accordingly so if you want to know about sentimental analysis then all of the comprehensive aspects about which I have told are really helpful for you. I invite everyone too much share your feedback that how you understand my post!

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Thanks

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